Overview

Brought to you by YData

Dataset statistics

Number of variables8
Number of observations30116
Missing cells161
Missing cells (%)0.1%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory3.0 MiB
Average record size in memory104.9 B

Variable types

Numeric8

Alerts

Bollinger_Lower is highly overall correlated with Bollinger_Middle and 2 other fieldsHigh correlation
Bollinger_Middle is highly overall correlated with Bollinger_Lower and 2 other fieldsHigh correlation
Bollinger_Upper is highly overall correlated with Bollinger_Lower and 2 other fieldsHigh correlation
MACD is highly overall correlated with MACD_Signal and 1 other fieldsHigh correlation
MACD_Signal is highly overall correlated with MACD and 1 other fieldsHigh correlation
RSI is highly overall correlated with MACD and 1 other fieldsHigh correlation
close is highly overall correlated with Bollinger_Lower and 2 other fieldsHigh correlation

Reproduction

Analysis started2025-02-16 20:37:39.795456
Analysis finished2025-02-16 20:37:52.370597
Duration12.58 seconds
Software versionydata-profiling vv4.12.2
Download configurationconfig.json

Variables

close
Real number (ℝ)

High correlation 

Distinct18180
Distinct (%)60.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean101.21491
Minimum0.69999999
Maximum688.37
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.4 MiB
2025-02-16T15:37:52.516095image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum0.69999999
5-th percentile6.5481251
Q136.86875
median68.209999
Q3131.04128
95-th percentile316.2225
Maximum688.37
Range687.67
Interquartile range (IQR)94.172533

Descriptive statistics

Standard deviation103.08751
Coefficient of variation (CV)1.0185013
Kurtosis5.9692034
Mean101.21491
Median Absolute Deviation (MAD)43.49
Skewness2.2056129
Sum3048188.1
Variance10627.035
MonotonicityNot monotonic
2025-02-16T15:37:52.745890image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
11.11999989 12
 
< 0.1%
2.279999971 12
 
< 0.1%
11.15999985 11
 
< 0.1%
46.40000153 11
 
< 0.1%
11.43000031 10
 
< 0.1%
46.5 10
 
< 0.1%
11.36999989 10
 
< 0.1%
11.31999969 10
 
< 0.1%
11.75 9
 
< 0.1%
10.89000034 9
 
< 0.1%
Other values (18170) 30012
99.7%
ValueCountFrequency (%)
0.6999999881 1
< 0.1%
0.7124999762 1
< 0.1%
0.7724999785 1
< 0.1%
0.8025000095 1
< 0.1%
0.8125 1
< 0.1%
0.8174999952 1
< 0.1%
0.8299999833 2
< 0.1%
0.8450000286 1
< 0.1%
0.8475000262 1
< 0.1%
0.8525000215 1
< 0.1%
ValueCountFrequency (%)
688.3699951 1
< 0.1%
687.4899902 1
< 0.1%
674.0800171 1
< 0.1%
673.5700073 1
< 0.1%
671.8800049 1
< 0.1%
671.0300293 1
< 0.1%
670.960022 1
< 0.1%
670.6699829 1
< 0.1%
669.8499756 1
< 0.1%
668.3200073 1
< 0.1%

RSI
Real number (ℝ)

High correlation 

Distinct29900
Distinct (%)99.3%
Missing13
Missing (%)< 0.1%
Infinite0
Infinite (%)0.0%
Mean51.758341
Minimum5.9879555
Maximum98.452877
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.4 MiB
2025-02-16T15:37:52.955676image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum5.9879555
5-th percentile29.714395
Q142.850914
median52.136534
Q361.004979
95-th percentile72.475108
Maximum98.452877
Range92.464921
Interquartile range (IQR)18.154066

Descriptive statistics

Standard deviation13.146475
Coefficient of variation (CV)0.25399723
Kurtosis0.009504711
Mean51.758341
Median Absolute Deviation (MAD)9.0608667
Skewness-0.16111812
Sum1558081.3
Variance172.82981
MonotonicityNot monotonic
2025-02-16T15:37:53.180847image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
49.27757469 3
 
< 0.1%
43.8400307 3
 
< 0.1%
39.65633309 3
 
< 0.1%
68.08326364 2
 
< 0.1%
63.31462921 2
 
< 0.1%
52.33340701 2
 
< 0.1%
41.73972757 2
 
< 0.1%
37.37605093 2
 
< 0.1%
65.03015887 2
 
< 0.1%
26.28597423 2
 
< 0.1%
Other values (29890) 30080
99.9%
(Missing) 13
 
< 0.1%
ValueCountFrequency (%)
5.987955507 1
< 0.1%
5.991088503 1
< 0.1%
5.99148493 1
< 0.1%
5.994874838 1
< 0.1%
6.02486913 1
< 0.1%
6.025151316 1
< 0.1%
6.029478212 1
< 0.1%
6.058037239 1
< 0.1%
6.087921314 1
< 0.1%
6.088633077 1
< 0.1%
ValueCountFrequency (%)
98.45287679 1
< 0.1%
98.33483621 1
< 0.1%
98.00772562 1
< 0.1%
97.3880566 1
< 0.1%
96.60290595 1
< 0.1%
96.57510053 1
< 0.1%
96.34524104 1
< 0.1%
95.84201492 1
< 0.1%
95.38728681 1
< 0.1%
95.21924336 1
< 0.1%

MACD
Real number (ℝ)

High correlation 

Distinct30091
Distinct (%)100.0%
Missing25
Missing (%)0.1%
Infinite0
Infinite (%)0.0%
Mean0.010532426
Minimum-162.66332
Maximum112.05284
Zeros0
Zeros (%)0.0%
Negative13073
Negative (%)43.4%
Memory size1.4 MiB
2025-02-16T15:37:53.387828image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum-162.66332
5-th percentile-5.5257823
Q1-0.61168744
median0.13584285
Q31.0090487
95-th percentile4.9864798
Maximum112.05284
Range274.71616
Interquartile range (IQR)1.6207361

Descriptive statistics

Standard deviation6.8416609
Coefficient of variation (CV)649.58073
Kurtosis166.60231
Mean0.010532426
Median Absolute Deviation (MAD)0.81652723
Skewness-3.7927617
Sum316.93123
Variance46.808324
MonotonicityNot monotonic
2025-02-16T15:37:53.579109image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
-3.794631956 1
 
< 0.1%
0.9832972665 1
 
< 0.1%
0.2123356814 1
 
< 0.1%
-0.656671483 1
 
< 0.1%
-1.359197978 1
 
< 0.1%
-1.365561331 1
 
< 0.1%
-1.75396606 1
 
< 0.1%
-2.14579984 1
 
< 0.1%
-2.524092086 1
 
< 0.1%
-2.75843487 1
 
< 0.1%
Other values (30081) 30081
99.9%
(Missing) 25
 
0.1%
ValueCountFrequency (%)
-162.6633242 1
< 0.1%
-162.4039144 1
< 0.1%
-161.0160433 1
< 0.1%
-159.6983563 1
< 0.1%
-157.8689595 1
< 0.1%
-153.9079405 1
< 0.1%
-153.6265552 1
< 0.1%
-148.5432294 1
< 0.1%
-144.2806397 1
< 0.1%
-142.8901025 1
< 0.1%
ValueCountFrequency (%)
112.0528362 1
< 0.1%
111.9734616 1
< 0.1%
111.8780409 1
< 0.1%
111.6397333 1
< 0.1%
111.0336205 1
< 0.1%
110.0476072 1
< 0.1%
108.1178289 1
< 0.1%
106.184078 1
< 0.1%
105.2570137 1
< 0.1%
104.8322604 1
< 0.1%

MACD_Signal
Real number (ℝ)

High correlation 

Distinct30083
Distinct (%)100.0%
Missing33
Missing (%)0.1%
Infinite0
Infinite (%)0.0%
Mean0.010210437
Minimum-142.44375
Maximum104.22788
Zeros0
Zeros (%)0.0%
Negative13180
Negative (%)43.8%
Memory size1.4 MiB
2025-02-16T15:37:53.810392image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum-142.44375
5-th percentile-5.1243051
Q1-0.57171173
median0.12833167
Q30.96890338
95-th percentile4.8064862
Maximum104.22788
Range246.67163
Interquartile range (IQR)1.5406151

Descriptive statistics

Standard deviation6.4126989
Coefficient of variation (CV)628.05331
Kurtosis149.75956
Mean0.010210437
Median Absolute Deviation (MAD)0.77553053
Skewness-3.5460614
Sum307.16058
Variance41.122707
MonotonicityNot monotonic
2025-02-16T15:37:54.063648image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
-3.92785674 1
 
< 0.1%
0.5223502359 1
 
< 0.1%
0.03787267871 1
 
< 0.1%
-0.4854914436 1
 
< 0.1%
-1.057532893 1
 
< 0.1%
-1.567740433 1
 
< 0.1%
-2.012759462 1
 
< 0.1%
-2.351781456 1
 
< 0.1%
-2.599927326 1
 
< 0.1%
-2.908518825 1
 
< 0.1%
Other values (30073) 30073
99.9%
(Missing) 33
 
0.1%
ValueCountFrequency (%)
-142.4437514 1
< 0.1%
-142.3321636 1
< 0.1%
-141.3253576 1
< 0.1%
-140.7793972 1
< 0.1%
-139.1717565 1
< 0.1%
-137.5676076 1
< 0.1%
-136.1650022 1
< 0.1%
-132.4922697 1
< 0.1%
-132.4773208 1
< 0.1%
-128.2523047 1
< 0.1%
ValueCountFrequency (%)
104.2278762 1
< 0.1%
104.0288255 1
< 0.1%
103.7388258 1
< 0.1%
103.1766042 1
< 0.1%
101.9151271 1
< 0.1%
101.4692322 1
< 0.1%
99.40054348 1
< 0.1%
98.66290563 1
< 0.1%
96.73877756 1
< 0.1%
95.73616901 1
< 0.1%

MACD_Diff
Real number (ℝ)

Distinct30083
Distinct (%)100.0%
Missing33
Missing (%)0.1%
Infinite0
Infinite (%)0.0%
Mean0.00031258173
Minimum-72.484431
Maximum44.314238
Zeros0
Zeros (%)0.0%
Negative14379
Negative (%)47.7%
Memory size1.4 MiB
2025-02-16T15:37:54.264776image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum-72.484431
5-th percentile-1.5378705
Q1-0.2214228
median0.010670895
Q30.26726528
95-th percentile1.6040314
Maximum44.314238
Range116.79867
Interquartile range (IQR)0.48868808

Descriptive statistics

Standard deviation2.1349055
Coefficient of variation (CV)6829.9114
Kurtosis266.86643
Mean0.00031258173
Median Absolute Deviation (MAD)0.24420515
Skewness-6.1551209
Sum9.4033962
Variance4.5578216
MonotonicityNot monotonic
2025-02-16T15:37:54.495053image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1.061128814 1
 
< 0.1%
1.937910229 1
 
< 0.1%
2.093456489 1
 
< 0.1%
2.288165798 1
 
< 0.1%
2.04083016 1
 
< 0.1%
1.780076114 1
 
< 0.1%
1.356087979 1
 
< 0.1%
0.9925834787 1
 
< 0.1%
1.234365995 1
 
< 0.1%
1.154552765 1
 
< 0.1%
Other values (30073) 30073
99.9%
(Missing) 33
 
0.1%
ValueCountFrequency (%)
-72.48443096 1
< 0.1%
-70.37571646 1
< 0.1%
-69.46991609 1
< 0.1%
-63.27777352 1
< 0.1%
-60.55139465 1
< 0.1%
-55.25455145 1
< 0.1%
-46.36808768 1
< 0.1%
-39.52733611 1
< 0.1%
-37.30199798 1
< 0.1%
-34.61529147 1
< 0.1%
ValueCountFrequency (%)
44.31423821 1
< 0.1%
41.90176606 1
< 0.1%
41.6872034 1
< 0.1%
40.69551284 1
< 0.1%
39.29787349 1
< 0.1%
33.87969542 1
< 0.1%
32.78462704 1
< 0.1%
31.73635176 1
< 0.1%
31.29846251 1
< 0.1%
27.81258007 1
< 0.1%

Bollinger_Upper
Real number (ℝ)

High correlation 

Distinct30055
Distinct (%)99.9%
Missing19
Missing (%)0.1%
Infinite0
Infinite (%)0.0%
Mean109.58993
Minimum1.0120627
Maximum967.1413
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.4 MiB
2025-02-16T15:37:54.764133image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum1.0120627
5-th percentile7.2411162
Q140.234435
median73.464848
Q3140.36309
95-th percentile342.37281
Maximum967.1413
Range966.12923
Interquartile range (IQR)100.12866

Descriptive statistics

Standard deviation112.78983
Coefficient of variation (CV)1.0291988
Kurtosis6.6383028
Mean109.58993
Median Absolute Deviation (MAD)46.287053
Skewness2.2906468
Sum3298328.3
Variance12721.545
MonotonicityNot monotonic
2025-02-16T15:37:54.998152image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
2.356133043 3
 
< 0.1%
2.224087497 3
 
< 0.1%
42.35735884 2
 
< 0.1%
53.30448114 2
 
< 0.1%
123.5463705 2
 
< 0.1%
2.789899116 2
 
< 0.1%
11.35971891 2
 
< 0.1%
177.6334434 2
 
< 0.1%
20.75580668 2
 
< 0.1%
22.17063186 2
 
< 0.1%
Other values (30045) 30075
99.9%
(Missing) 19
 
0.1%
ValueCountFrequency (%)
1.012062746 1
< 0.1%
1.018998554 1
< 0.1%
1.031165496 1
< 0.1%
1.03399711 1
< 0.1%
1.040650531 1
< 0.1%
1.042906193 1
< 0.1%
1.04441639 1
< 0.1%
1.048809025 1
< 0.1%
1.054293183 1
< 0.1%
1.058112075 1
< 0.1%
ValueCountFrequency (%)
967.1412963 1
< 0.1%
966.6379075 1
< 0.1%
958.2962602 1
< 0.1%
956.3579665 1
< 0.1%
937.6595471 1
< 0.1%
936.4551838 1
< 0.1%
913.5073466 1
< 0.1%
898.6090136 1
< 0.1%
888.9530494 1
< 0.1%
858.7711189 1
< 0.1%

Bollinger_Lower
Real number (ℝ)

High correlation 

Distinct30055
Distinct (%)99.9%
Missing19
Missing (%)0.1%
Infinite0
Infinite (%)0.0%
Mean92.886492
Minimum-347.17276
Maximum645.43874
Zeros0
Zeros (%)0.0%
Negative186
Negative (%)0.6%
Memory size1.4 MiB
2025-02-16T15:37:55.225646image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum-347.17276
5-th percentile5.0724525
Q133.795974
median63.511805
Q3121.01471
95-th percentile296.05467
Maximum645.43874
Range992.61149
Interquartile range (IQR)87.218736

Descriptive statistics

Standard deviation95.70842
Coefficient of variation (CV)1.0303804
Kurtosis5.9073868
Mean92.886492
Median Absolute Deviation (MAD)41.453745
Skewness2.1101662
Sum2795604.8
Variance9160.1016
MonotonicityNot monotonic
2025-02-16T15:37:55.425852image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
2.235866869 3
 
< 0.1%
1.583912472 3
 
< 0.1%
41.74664125 2
 
< 0.1%
50.83251875 2
 
< 0.1%
116.5856295 2
 
< 0.1%
2.344100947 2
 
< 0.1%
11.03528107 2
 
< 0.1%
149.8665566 2
 
< 0.1%
19.01659322 2
 
< 0.1%
20.74376824 2
 
< 0.1%
Other values (30045) 30075
99.9%
(Missing) 19
 
0.1%
ValueCountFrequency (%)
-347.1727554 1
< 0.1%
-346.6162026 1
< 0.1%
-339.6674225 1
< 0.1%
-337.0391054 1
< 0.1%
-326.1061619 1
< 0.1%
-315.8375977 1
< 0.1%
-305.7841135 1
< 0.1%
-278.8350447 1
< 0.1%
-278.5006198 1
< 0.1%
-246.2353405 1
< 0.1%
ValueCountFrequency (%)
645.4387396 1
< 0.1%
645.3542066 1
< 0.1%
644.1652848 1
< 0.1%
643.8180315 1
< 0.1%
642.2948791 1
< 0.1%
641.7301158 1
< 0.1%
640.8582139 1
< 0.1%
637.1920891 1
< 0.1%
637.153253 1
< 0.1%
635.4628704 1
< 0.1%

Bollinger_Middle
Real number (ℝ)

High correlation 

Distinct29817
Distinct (%)99.1%
Missing19
Missing (%)0.1%
Infinite0
Infinite (%)0.0%
Mean101.23821
Minimum0.9065
Maximum666.77749
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.4 MiB
2025-02-16T15:37:55.626090image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum0.9065
5-th percentile6.607875
Q137.0775
median68.543
Q3131.359
95-th percentile315.8714
Maximum666.77749
Range665.87099
Interquartile range (IQR)94.2815

Descriptive statistics

Standard deviation102.50105
Coefficient of variation (CV)1.012474
Kurtosis5.8244661
Mean101.23821
Median Absolute Deviation (MAD)43.487
Skewness2.1828314
Sum3046966.5
Variance10506.466
MonotonicityNot monotonic
2025-02-16T15:37:55.848236image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
2.30249995 3
 
< 0.1%
307.5 3
 
< 0.1%
1.903999984 3
 
< 0.1%
163.675 3
 
< 0.1%
2.295999956 3
 
< 0.1%
11.19349999 3
 
< 0.1%
11.18800001 3
 
< 0.1%
163.775 3
 
< 0.1%
1.800000006 3
 
< 0.1%
55.57999992 2
 
< 0.1%
Other values (29807) 30068
99.8%
(Missing) 19
 
0.1%
ValueCountFrequency (%)
0.9064999998 1
< 0.1%
0.9082499981 1
< 0.1%
0.9113750011 1
< 0.1%
0.9123750001 1
< 0.1%
0.9137500018 1
< 0.1%
0.9150000006 1
< 0.1%
0.9161249995 1
< 0.1%
0.9171250015 1
< 0.1%
0.9206250012 1
< 0.1%
0.9220000029 1
< 0.1%
ValueCountFrequency (%)
666.7774933 1
< 0.1%
665.9424927 1
< 0.1%
665.0919952 1
< 0.1%
663.8999939 1
< 0.1%
663.6094971 1
< 0.1%
661.8659943 1
< 0.1%
661.7529968 1
< 0.1%
661.0629944 1
< 0.1%
660.6119995 1
< 0.1%
660.321994 1
< 0.1%

Interactions

2025-02-16T15:37:50.072438image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-16T15:37:40.579549image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-16T15:37:41.820537image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-16T15:37:42.950968image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-16T15:37:44.128561image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-16T15:37:45.311005image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-16T15:37:47.341321image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-16T15:37:48.813234image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-16T15:37:50.243376image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-16T15:37:40.737365image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-16T15:37:41.968676image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-16T15:37:43.105398image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-16T15:37:44.288712image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-16T15:37:45.465121image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-16T15:37:47.503166image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-16T15:37:48.993623image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-16T15:37:50.396291image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-16T15:37:40.882899image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-16T15:37:42.090635image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-16T15:37:43.246405image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-16T15:37:44.431418image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-16T15:37:45.610214image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-16T15:37:47.660274image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-16T15:37:49.154255image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-16T15:37:50.556220image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-16T15:37:41.038980image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-16T15:37:42.231397image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-16T15:37:43.385489image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-16T15:37:44.576063image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-16T15:37:45.757788image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-16T15:37:47.829116image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-16T15:37:49.333483image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-16T15:37:50.722942image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-16T15:37:41.191639image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-16T15:37:42.371075image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-16T15:37:43.537978image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-16T15:37:44.719641image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-16T15:37:45.908227image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-16T15:37:47.988861image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-16T15:37:49.471853image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-16T15:37:50.874414image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-16T15:37:41.352729image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-16T15:37:42.511261image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-16T15:37:43.682623image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-16T15:37:44.856488image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-16T15:37:46.045668image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-16T15:37:48.304776image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-16T15:37:49.623386image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-16T15:37:51.099327image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-16T15:37:41.507067image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-16T15:37:42.655007image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-16T15:37:43.828809image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-16T15:37:45.008626image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-16T15:37:47.006749image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-16T15:37:48.467322image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-16T15:37:49.773616image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-16T15:37:51.279153image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-16T15:37:41.665776image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-16T15:37:42.795529image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-16T15:37:43.972369image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-16T15:37:45.151802image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-16T15:37:47.174481image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-16T15:37:48.625748image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-16T15:37:49.922324image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Correlations

2025-02-16T15:37:56.009626image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Bollinger_LowerBollinger_MiddleBollinger_UpperMACDMACD_DiffMACD_SignalRSIclose
Bollinger_Lower1.0000.9800.9600.160-0.0450.1760.0750.982
Bollinger_Middle0.9801.0000.9950.151-0.0450.1680.0610.991
Bollinger_Upper0.9600.9951.0000.144-0.0420.1590.0500.984
MACD0.1600.1510.1441.0000.2390.9260.7840.201
MACD_Diff-0.045-0.045-0.0420.2391.000-0.0040.4810.008
MACD_Signal0.1760.1680.1590.926-0.0041.0000.6510.203
RSI0.0750.0610.0500.7840.4810.6511.0000.120
close0.9820.9910.9840.2010.0080.2030.1201.000

Missing values

2025-02-16T15:37:51.565474image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
A simple visualization of nullity by column.
2025-02-16T15:37:51.898049image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.
2025-02-16T15:37:52.184594image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
The correlation heatmap measures nullity correlation: how strongly the presence or absence of one variable affects the presence of another.

Sample

closeRSIMACDMACD_SignalMACD_DiffBollinger_UpperBollinger_LowerBollinger_Middle
dateTicker
2015-01-02A40.560001NaNNaNNaNNaNNaNNaNNaN
2015-01-05A39.799999NaNNaNNaNNaNNaNNaNNaN
2015-01-06A39.180000NaNNaNNaNNaNNaNNaNNaN
2015-01-07A39.700001NaNNaNNaNNaNNaNNaNNaN
2015-01-08A40.889999NaNNaNNaNNaNNaNNaNNaN
2015-01-09A40.590000NaNNaNNaNNaNNaNNaNNaN
2015-01-12A40.110001NaNNaNNaNNaNNaNNaNNaN
2015-01-13A39.549999NaNNaNNaNNaNNaNNaNNaN
2015-01-14A39.060001NaNNaNNaNNaNNaNNaNNaN
2015-01-15A38.009998NaNNaNNaNNaNNaNNaNNaN
closeRSIMACDMACD_SignalMACD_DiffBollinger_UpperBollinger_LowerBollinger_Middle
dateTicker
2023-12-15MMM89.44815875.8578342.6222502.2258440.39640690.48562577.33210383.908864
2023-12-18MMM88.52006570.2481602.6137322.3034210.31031090.92287577.77528884.349081
2023-12-19MMM88.83779171.0377742.6026172.3632600.23935691.26127178.37919984.820235
2023-12-20MMM86.68060359.4929622.3921662.3690420.02312491.03467879.41515785.224917
2023-12-21MMM88.26087264.0962202.3260832.360450-0.03436791.02267280.27916985.650920
2023-12-22MMM88.90467865.8013322.2991582.348192-0.04903391.01775481.15197986.084867
2023-12-26MMM90.39297569.4171732.3705872.3526710.01791691.27364081.81917086.546405
2023-12-27MMM90.91973170.6019162.4415542.3704470.07110791.65868782.28947586.974081
2023-12-28MMM91.71405072.3418762.5326962.4028970.12979992.05297982.83331087.443144
2023-12-29MMM91.40467870.5894862.5505622.4324300.11813292.27697383.46633887.871656